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Identification of Canadian wheat varieties using OpenArray genotyping technology
Accurate and efficient means to determine the variety composition of wheat composites are required to provide assurances in the grain handling system. We developed a variety identification system for hexaploid wheat (Triticum aestivum L.) that operates with a simple workflow and can sustain a high l...
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Published in: | Journal of cereal science 2015-09, Vol.65, p.267-276 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Accurate and efficient means to determine the variety composition of wheat composites are required to provide assurances in the grain handling system. We developed a variety identification system for hexaploid wheat (Triticum aestivum L.) that operates with a simple workflow and can sustain a high level of throughput. A set of 32 SNP genotyping assays was developed for use with the TaqMan OpenArray genotyping system. A reference profile database was constructed based on a survey of these markers in 24 kernels of each of 128 wheat varieties representing four market classes. Custom software was written to generate allele profiles from exported OpenArray fluorescence data and query those profiles against the reference database to produce variety calls. We demonstrated the effectiveness of the system in blind analyses of 192 kernels comprising 119 varieties. Each kernel was correctly identified with the exception of two that were called as unidentified and were later confirmed to have uncommon variant profiles not previously encountered.
•Canadian wheat varieties were resequenced to identify polymorphisms.•TaqMan genotyping assays were designed and tested on the OpenArray platform.•32 selected markers were used to create reference profiles of 128 varieties.•Custom software was developed to call alleles and varieties from OpenArray data.•Accuracy of variety calls was demonstrated through blind sample analyses. |
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ISSN: | 0733-5210 1095-9963 |
DOI: | 10.1016/j.jcs.2015.08.002 |